Today's text-to-speech synthesis technology is capable of resembling human speech. These systems are being targeted for use in embedded devices such as Personal Digital Assistants (PDAs), cell phones, home appliances, and many other devices. A problem that many of these systems encounter is limited memory space. Most of today's embedded systems face stringent constraints in terms of limited memory and processing speed provided by the devices in which they are designed to operate. These constraints have typically limited the use of multilingual text-to-speech systems.
Each language supported by a text-to-speech system normally requires an engine to synthesize that language and a database containing the sounds for that particular language. These databases of sounds are typically the parts of text-to-speech systems that consume the most memory. Therefore, the number of languages that a text-to-speech system can support is closely related to the size and related memory requirements of these databases. Therefore, a need remains for a multilingual text-to-speech system and method that is capable of supporting multiple languages while minimizing the size and/or number of sound databases. The present invention fulfills this need.